Test inception module B

examples/inception_v3/tests/inception_b.py

@@ -0,0 +1,43 @@
+import sys
+
+import torch
+from torchvision.models.inception import InceptionB
+
+sys.path.append("../../../tools")
+from utils import print_cpp_vector
+
+torch.manual_seed(0)
+
+@torch.no_grad()
+def init_weights(m):
+    if isinstance(m, torch.nn.Conv2d):
+        torch.nn.init.uniform_(m.weight)
+    elif isinstance(m, torch.nn.BatchNorm2d):
+        torch.nn.init.uniform_(m.weight)
+        torch.nn.init.uniform_(m.bias)
+
+with torch.no_grad():
+    inception_b = InceptionB(3)
+    inception_b.apply(init_weights)
+
+    # branch3x3
+    print_cpp_vector(torch.flatten(inception_b.branch3x3.conv.weight), "branch3x3_conv_weights")
+    print_cpp_vector(torch.flatten(inception_b.branch3x3.bn.weight), "branch3x3_bn_weights")
+    print_cpp_vector(torch.flatten(inception_b.branch3x3.bn.bias), "branch3x3_bn_bias")
+
+    # branch3x3dbl
+    print_cpp_vector(torch.flatten(inception_b.branch3x3dbl_1.conv.weight), "branch3x3dbl_1_conv_weights")
+    print_cpp_vector(torch.flatten(inception_b.branch3x3dbl_1.bn.weight), "branch3x3dbl_1_bn_weights")
+    print_cpp_vector(torch.flatten(inception_b.branch3x3dbl_1.bn.bias), "branch3x3dbl_1_bn_bias")
+
+    print_cpp_vector(torch.flatten(inception_b.branch3x3dbl_2.conv.weight), "branch3x3dbl_2_conv_weights")
+    print_cpp_vector(torch.flatten(inception_b.branch3x3dbl_2.bn.weight), "branch3x3dbl_2_bn_weights")
+    print_cpp_vector(torch.flatten(inception_b.branch3x3dbl_2.bn.bias), "branch3x3dbl_2_bn_bias")
+
+    input_shape = (1, 3, 8, 8)
+    input = torch.randn(input_shape)
+    print_cpp_vector(torch.flatten(input), "input")
+
+    output = inception_b(input)
+    output = torch.flatten(output)
+    print_cpp_vector(output, "expected")

examples/inception_v3/tests/test_inception_a.cpp

@@ -94,8 +94,6 @@ class InceptionATest : public ::testing::Test {
         inception_a =
             new InceptionA(inputShape, inputChannels, poolFeatures, prefix);
 
-        CUDANet::Layers::Conv2d *conv;
-
         // Set up layer weights and bias
         // Branch 1x1
         setBasicConv2dWeights(branch1x1_conv_weights, branch1x1_bn_weights,